DRIC Report

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Wilbur Smith Associates Report on

Comprehensive Traffic and Toll Revenue Study:

Windsor Gateway Project

A Critical Evaluation

Submitted to

Sierra Club Canada

Submitted by

Econometric Research Limited

September, 2010


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Executive Summary

Econometric Research Ltd (ERL) was retained by the Sierra Club Canada (SCC) to review the

report prepared by Wilbur Smith Associates (WSA) entitled "Comprehensive Traffic and TollRevenue Study-Windsor Gateway" dated January, 2009 (WSA 2009) and its Appendices.

The 2009 WSA report was prepared pursuant to a Request for Proposals issued by TransportCanada in 2008 to provide a traffic and revenue forecast for use in the future procurement of apublic-private partnership for the new Detroit River Crossing. The WSA 2009 report indicatesthat it drew upon previous studies, being the Planning and Needs Feasibility Study, the DetroitRiver International Crossing Study, and other transportation modeling studies that wereconducted further to the environmental process. These previous studies were all considered injustifying the need for the project.

ERL also reviewed the May 2010 Appendices of a later WSA Report, produced for the MichiganDepartment of Transportation, for the new crossing. The May 2010 Appendices provided oneadditional year of data points ending in 2008, as compared to the January 2009 Appendices,which ended in 2007. The May 2010 report adjusted forecasts downward in 2009 as thepredictions from the earlier work had not borne out, though still projected continuous upwardgrowth after that point. But for this one minor difference between the Appendices, they areidentical in their methodologies and assumptions, and our conclusions apply equally to both.

Specifically ERL was tasked with evaluating the travel demand forecasts of the Report and hasassembled a team of specialists to undertake this assignment consisting of Dr. Atif Kubursi(Professor of Economics, McMaster University and President of Econometric Research Limited),

Dr. Pavlos Kanaroglou (Professor and Director of the School of Geography and Earth Sciences,McMaster University and Director of the McMaster Institute for Transportation and Logistics(MITL)), and Dr. Abe Mouaket (Transportation Engineer and President of Innovative Methods).

The ERL team focused on the structure of the travel demand model used, the data selected forestimation and projection exercises, the assumptions made, the exact specification of the variousequations, the regression techniques chosen, the estimated results and the forecasting scenarios.

The analysis and review considered many aspects of the WSA study and reached a number ofconclusions.

What emerges from our review is that there appears to be an attempt by the WSA Team torationalize an investment of several billions of dollars in a new crossing that is anchored onoptimistic forecasts of crossing volumes in the frontier region. The WSA forecast ignores theserious structural changes of the decade of 2000-2010, selectively chooses independentpredictive variables with positive historical trends and eliminates other relevant variables fromthe forecasting equations which could introduce dampening effects.

A brief review of the analysis and conclusions reached are summarized below:


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In any projection or forecast, the past is typically considered as the best guide for thefuture. Time series data are examined using regression analysis in order to identify andquantify the systemic determinants of the dependent variables of interest during theperiod for which data exists. The crucial dependent variables in WSA Report are: The

passenger traffic volumes and the commercial vehicle volumes at the three existingcrossings in the Windsor-Detroit-Sarnia area the Ambassador Bridge (AB), andWindsor-Detroit Tunnel (WDT), and Blue Water Bridge (BWB).

The development of a new crossing in the region needs to be contingent on a forecastthat shows that traffic volumes in the future are likely to be greater than the existingtraffic capacity of the current three crossings.

The new crossing will have to be based on a strong stated preference for a crossing thatlinks more quickly to the highway network on both sides of the Detroit River and that itis cost effective.

The WSA team has developed its work with these objectives in mind. Unfortunately, thepast did not cooperate well with their plans. The developments in the region in the pastdecade have been a tale of declining traffic, both for the passenger and for thecommercial vehicle components. These declines were not exclusively conjectural(cyclical); they reflect some deep structural developments and some unique changes thatare not expected to change course easily or quickly. These structural and unique changescan not be ignored; they need to be worked into the model and into the futureprojections. Unfortunately most of these changes are ignored by WSA. Most of theirfuture projections are overly optimistic and ignore the difficult decade of 2000-2010.

A number of factors have contributed to the reversal of past growth performancebetween 2000 and 2008. While some of these factors may be dismissed as transitory andcyclical in nature, quiet a few others are more permanent structural factors and couldbecome ingrained into the normal processes of the system.

Several socio-economic significant events have occurred since 2000 that have greatlyaffected the volumes of car and commercial traffic observed on the crossings betweenthe US and Canada and particularly in Detroit-Windsor corridor. Some of these wererecognized by the WSA team, but many were not considered; and in all there is thepresumption that their negative influences and impacts may not last long.

A short list of these socio-economic significant events, with our expectation that theywill continue to contribute to declining traffic volumes, includes:o Opening of Detroit Casinos The opening of the MGM Grand Detroit Casino in

July of 1999 effectively ended the need for Detroit and other US residents to crossthe border to gamble at Casino Windsor, which started operations in 1994. Inaddition, two new casinos have opened in Detroit. It is not surprising that the


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opening of the new Detroit casinos has had a noticeable, if not permanent impacton discretionary traffic volumes;

o The Stubborn Recession The economy took a significant downturn in 2000after very strong growth in the 1990s, starting from the dot-com debacle, then

the Enron collapse on December 2, 2002, and then the sub-prime fiasco, whichhas cascaded to bank failures and the economic collapse of countries around theworld. Historically high levels of unemployment over the prevailing nationalaverages were registered in Detroit and Windsor. While the attraction of Detroitas an employment center for Windsor residents had remained stable until 2006, itquickly contracted thereafter and many Canadians and local residents lost theirjobs. The recovery is still slow and particularly in the job market. The prospectsof a job creating recovery has now been pushed further into the future and thereare serious doubts that the region will ever recover fully;1

o 9/11, the Iraq War and the Afghanistan War While traffic decline began tooccur in 1999,the aftermath of the September 11, 2001, and two related wars, hasseriously impacted the ease with which travelers can cross the border and has alsodepressed the propensity for international discretionary travel;

o SARS and Swine Flu epidemics in Toronto In 2003, the city of Toronto, apopular tourist destination for Americans, was one of several global locations ofthe highly-publicized epidemic. Impacts on tourism and vacation trips across theborder were immediate and will have some long lasting impacts;

o Appreciation of the Canadian dollar In 2007, the value of the Canadian dollarhit parity with the US dollar for the first time since the mid- 1970s and for a shortwhile it even exceeded parity reaching $1.10 US per one Canadian dollar. Whilethe rise in the value of the Canadian dollar vis--vis the US dollar makes travel tothe US more attractive for Canadians, it has the opposite effect for travel toCanada for Americans. From a work commuting perspective, the incentive forCanadians to work in the US will decrease and Canadian exports to the US willrise in price and become less attractive. On the other hand, Canadians will beinduced to increase their cross border shopping and importation of US goods;

o Passport requirement The introduction of a passport requirement in mid 2010on cross border traffic is turning out to be a major barrier to travel between thetwo countries. This is particularly so given the low propensity of US residents toacquire this document. It is believed that that no more than 22% of US citizens dohave a passport and are not likely to acquire one soon;2

1 See US Bureau of Labor Statistics, Press Release http://www.bls.gov/news.release/empsit.nr0.htm and PaulKrugman, The Return of Depression Economics and the Crisis of 2008. New York Times, April 18, 20082 Testimony of Frank E. Moss, Deputy Assistant Secretary for Passport Services, Bureau of Consular Affairs: Iwould like to note that even though only 68 million Americans have passports in

http://travel.state.gov/law/legal/testimony/testimony_2922.html.


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o Increase in gasoline prices While gasoline prices have fluctuated widely, thereis a general escalating trend. This is all the more likely with the increasedrealization that we are not adding to proven reserves what we are depleting.There are also the looming emission charges and carbon taxes. Transportationvolumes are quite sensitive to gas prices and the expected rise in these prices as

world wide scarcity rises suggest that crossing volumes may decline in tandemwith these expected increases in gas prices;3

o Technological Change The Internet has reduced measurably the cost ofcommunication so much so that it is now the dominant means of humaninteraction. The increased use of the Internet and the continuous decline in its costhas and will continue to boost its competitive attractiveness over traditionaltransportation modes of interaction. The increased share of services in total GDPis another factor that would continue to decrease the intensity of transportation;

o The Disappearing Middle Class Income and wealth in both Canada and theUnited States have increasingly gravitated into the hands of the few rich. The poorhave become poorer and the rich richer. The middle class suffered major losses inreal income whereas the top 20th percentile on the income distribution scale hasexpanded its income and wealth shares.4 The rich typically fly and the poor rarelydrive. Passenger cars are generally owned and driven by the middle class. Asglobalization has been associated with income and wealth polarization, the middleclass has shrunk;5

o Environmental Issues - Increased awareness of the impact of transportation onthe environment is likely to convince people to travel less and to use other lessintrusive modes of transportation (e.g., trains). The implications of environmentalawareness bolstered by emission taxes, carbon charges, etc. must be factored intoany forecast of future traffic volumes in any jurisdiction.

Many of the factors listed above were not considered important and were therefore notincluded in the set of independent variables.

The impacts of these events on annual crossing volumes have already becomenoticeable. Since 2000, passenger car traffic volumes have decreased by 35% at theAmbassador Bridge, 48% Detroit-Windsor tunnel, and 22%, at the Blue Water Bridge.The continuation of these negative impacts on future volumes is quite likely as many ofthese structural factors continue to exert their influence. But WSA did not bother to

3 Gene Coperman in http://www.ccs.neu.edu/home/gene/peakoil/4 The US Census Bureaus measurement of the Gini coefficient, a widely-used indicator of income inequality rosesteadily from a level of 0.388 in 1968 to 0.466 in 2001. Seehttp://www.census.gov/hhes/www/income/histinc/ie1.html

5Mode of transport is income determined seehttp://www.payscale.com/research/CA/Country=Canada/Salary/by_Method_of_Travel


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include many of these factors in their analysis and forecasts despite the overwhelmingevidence as to their relevance.

Three separate types of traffic volumes were identified and their growth rates wereestimated. The three types include:

o Passenger vehicle crossings occurring within the same dayo Passenger vehicle crossings with a trip duration exceeding the same day

(overnight trips)o Commercial truck crossings

People travel short or long distances for a variety of reasons, whether for commuting towork, recreation, or other reasons. Many socioeconomic determinants can be postulatedto influence this travel. Typically, same day travel is dominated by work considerationand this is a function of such variables as income, exchange rates, cost of fuel,employment prospects, and many other quantifiable or non-quantifiable factors.

Unfortunately the Centre for Spatial Economics (Centre) has selected a small subset ofthese factors in its estimation and concentrated on independent variables with upwardtrends that biased the forecasts upward.

The Centre used multivariate regression analysis to quantify these determinants andprojected the independent factors into the future in order to forecast the future volumes ofcross border traffic in the Detroit Windsor region.

The data used was collected from many sources and many assumptions were used togenerate a time series set for estimation and projection. Many of these assumptions arearbitrary and unreasonable; they compromised the accuracy and reliability of the data set.

A short list of these assumptions includes: Same day and overnight passenger car travelers characteristics of those entering

the US from Canada are the same as for travelers entering into Canada from theUS. This assumption skews the results because there are more short trips fortravelers entering into the US than the US entering Canada, so to use the samevariable skews the results.

Automobile occupancy rates for both US and Canadian travelers are identical.This is may not be a critical assumption but it can still bias the results given the

expected escalation in the cost of fuel, the rise in the cost effectiveness of travel ofsmaller parties and the different purposes of travelers.

Non-Canadian/US residents traveling into Canada have the same travelcharacteristics as those surveyed. This may be true, but the proportions of these tothe total are too small to make a major difference in the results. It is not correct orreasonable, however, to expect non-Canadian and US travelers to exhibit the same


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characteristics as those surveyed. They generally travel for different reasons andpurposes than those who were surveyed.

The Michigan Ontario Border Crossing Survey results of 2000 were used togenerate volume flows and characteristics for later years. The most glaring

inherent assumption was that pertaining to the proportion of commute/work tripsin the survey. These were considered to be representative of that proportion forthe entire year and beyond, which we believe to be an unreasonable assumption.

The Origin-Destination survey trip purpose data was also used to split thepassenger car traffic for 2008 with an adjustment to account for weekends. Theinterim years between 2000 and 2008 were interpolated based on the data in 2000.

The Centre claimed that multiple possible socioeconomic variables were tested (200multivariate equations were modeled with permutations of the independentsocioeconomic variables for each same day passenger vehicle crossing purpose) to

determine a statistically significant historical correlation with the border crossingvolumes. However, this appears to be only a claim as the Report and Appendix C do notreport on any of these estimated equations.

The Centre has chosen to report on only one equation for the frontier and for each trafficvolume type based on the socioeconomic variables that exhibited the best explanatory power. The Centre did so, based on what it claims as its qualitative and quantitativeassessments of the regression results. This is problematic because only the variablesshowing increasing trends in traffic volumes were used while the variables showing anydecreasing trend were ignored.

The regression results of the first estimated equation show that 91% of the variations inthe same day passenger traffic in the frontier are explained by the combined Michiganand Ontario employment alone.

o This specification showing one variable explaining this much of the variation ofsame day traffic (commute/work related traffic) on its own is subject to manyqualifications. It is typically the case that in a regression equation with missingvariables, one single explanatory variable can easily pick up the implicitinfluences of the variations in the missing variables.

o Equally problematic is the fact that the single determinant in the first equation is avariable that typically displays a positive trend which biases the projections of thistraffic volume upward, without a single negative influence of the typeexperienced and reflected in the data on the volumes of passenger same daycrossings after 1999.

The regression results do not include relevant diagnostic statistics such as the DurbinWatson measure that would have pointed out whether or not the single variable chosen issufficient to eliminate any systematic errors in the residuals. Exclusion of such


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diagnostic statistics would have to mean that there are no other independent variablesneeded to improve the regression accuracy or to eliminate any bias in the estimatedcoefficient. This cannot be known without the diagnostic statistic.

A number of key variables were considered to be potential explanatory and predictivevariables for overnight passenger car crossings. These include the populations ofMichigan and Ontario, the employment levels in both of these areas, their real GDP, theexchange rate and a dummy variable for 9/11.

The Centre has claimed that different pairings of these variables were tested. But giventhe number of observations, it is not clear why pairings of two and not more than twoexplanatory variables were used in the regression equations.

Again the Centre claimed that in the end the greatest explanatory power of historicalovernight passenger car crossings came from the combined populations of Ontario andMichigan. This variable explained only 68% of the total variation in the dependent

variable. This is not a whole lot in time series regressions.

The Centre also claimed that none of the other variables explained the brief rise aboveand the fall below the long term trend. But this claim was not demonstrated.

No other functional forms (non-linear) were specified and estimated. The linear structureused is simply inappropriate as the predicted values diverged markedly from the actualvalues. If the real issue is forecasting accuracy, then other statistical specifications shouldhave been used such as Vector Auto Regression (VAR), Box-Jenkins, ARIMA. We notethat some of the earlier DRIC studies did that with some success and good outcomes.

Nothing but a positive and continuous trend in the volume of overnight passenger carcrossings can come from the baseline forecasts used in the projections. Despite theevident fluctuations and the dip in the volumes of crossings in overnight passengervehicles in the 2000s, the forecast is for a continuously rising volume of these crossings.It is true that the slope of the rise is limited but there are serious doubts as to the validityof using a continuously rising explanatory variable to predict the future volumes whenthe past is essentially a truly camel humped distribution.

The explanatory variables of the volume of commercial vehicle crossings along thefrontier are the turnover of Ontarios foreign trade and the exchange rate. Both of thesevariables are highly significant. The Ontario foreign trade turnover has a t-statistic of

over 29.4 and that of the exchange rate of about 6.

The adjusted R2 is quite high in this equation and it is without doubt the best regression fitof all the three traffic components. It is not surprising therefore to see that the actual andestimated curves are quite close and the predicted volumes tracks well and fully with theactual data.


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Given the close relationship between trade turnover and commercial vehicle crossingsand the common patterns they share, predicting correctly the turnover of foreign tradeprovides a solid anchor for predicting commercial vehicle crossings. But predicting theturn over of trade depends on predicting correctly its determinant, which in this case isthe real US GDP growth rate. The projected real rate of growth of the US GDP is a

modest 1% per year for the long term. This does not justify the overly optimisticprojection of the turn over volume of US-Canada trade.

The same problems alluded to earlier afflict the projections of the independent(exogenous) variables driving the forecast in the case of future commercial vehiclecrossings. Again the predicted turnover of trade is an upward and smooth trend and italone is carrying the brunt of the forecasts of the commercial vehicle crossings. We arenot sure what happened to the exchange rate variable. It was dropped as in other forecastson the presumed proposition that its fluctuations are considered to be of a short termnature.

The Centre accepted the low real US GDP rates of growth projected by the CongressionalBudget Office, but this acceptance was not reflected in its projections of the trade turnover volumes that determine the volume of commercial vehicle crossings in the frontierregion.

The future is uncertain and the projected values are subject to errors. Some are embodiedin the estimated coefficients (with standard errors) and others are about the trends in theexogenous (independent) variables.

The Centre has chosen to use an outmoded and now generally unaccepted way to dealwith the future and risks. Using arbitrary pessimistic and optimistic variations does not

help much. Were the investment values at stake in the order of magnitude of a fewmillion dollars, the use of sophisticated risk analysis may not be warranted. The expectednew investment in the new bridge is in the order of more than $5 billion of which $1.6billion is Ontarios share alone and it does not include the federal share of expenditures.Forecasting errors are quite costly and therefore simple forecasts can not and should notunderpin massive investments of the kind and value expected to be made in the newcrossing.

We are of the opinion that a full and thorough risk assessment procedure is necessary andwarranted. The current alternative forecasts in the WSA Report are not consistent withthe current standard risk analysis procedures. The latter calls for using the standard errors

in the regression equations and different probability distributions assigned to theexogenous variables. A standard tool is @RISK which is now widely used and is thestandard tool in this area, but was not used here.

The what if and sensitivity analyses in the WSA Report are not sufficient to deal withthe risks embedded in this massive project and the type of forecasts and analysesundertaken. There is no way that sensitivity analysis, however useful it may be, cansubstitute for the proper risk analysis that should have been undertaken.


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The stated preferences survey through which data were collected used an orthogonalexperimental design, implying that the independent variables used in the estimateddiscrete choice models were uncorrelated. It is not clear to us how the survey participantswere randomly selected for inclusion in the sample. Like any other econometric modeling

activity, a random sample is necessary, if one is to avoid bias in the parameter estimates.This is not clearly the case in the stated preference survey conducted by ResourceSystems Group Inc. (RSG).

Apart from the alternative specific constants, all models presented in the RSG Reportused two independent variables: the travel time, or time to cross to the other side, and tollcost. Although the RSG Report mentions that several other variables were tested, none ofthose specifications are presented. In particular, trip characteristics and socioeconomicand demographic characteristics of the individuals in the case of the private automobilemodels should have been used.

The view of someone who lives far from the area and very infrequently uses one of thosecrossings would be very different from that of someone who lives in the area. Also,valuation of time and toll cost are different for different socio-economic classes. Unlesssuch variables had no impact on the presented coefficients, then the exclusion of suchvariables from the models risks rendering them as mis-specified. At this juncture it is ourconsidered judgment that they are mis-specified.

In all of the models presented one of the major drawbacks has been the lack of modeldiagnostics. Without exception, the initial and final value of the log-likelihood function is presented for each estimated model. One can certainly calculate from these values theoverall improvement in the model (2). However, the most often used measure of

goodness-of-fit for such models is the improvement in the log-likelihood function aftertaking into account the alternative specific constants. This was not included in the Report.

Our most worrisome concern here is the use of the stated preference model for predictionand allocation of market shares among the crossings, which is totally unacceptable.


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Introduction

The Wilbur Smith Associates (WSA) team comprising WSA, IBI Group, Resource SystemsGroup Inc., and the Centre for Spatial Economics was retained by Transport Canada in

coordination with the Canada-US-Ontario-Michigan Border Transportation Partnership (thePartnership) to conduct an Investment-Grade Level Traffic and Revenue Study for the newproposed Detroit River International Crossing (DRIC) within the Windsor-Detroit region. TheReport was part of Transport Canadas ongoing initiatives to collect and update data andanalyses to support an evaluation of the traffic and revenue potential of the WGBC as part of thePartnerships intention to undertake to fund and build the proposed bridge infrastructure.

Econometric Research Ltd (ERL) was retained by the Sierra Club Canada (SCC) to review thereport prepared by Wilbur Smith Associates (WSA) entitled "Comprehensive Traffic and TollRevenue Study-Windsor Gateway" dated January, 2009 and its Appendices.

The 2009 WSA report was prepared pursuant to a Request for Proposals issued by TransportCanada in 2008 to provide a traffic and revenue forecast for use in the future procurement of apublic-private partnership for the new Detroit River International Crossing (DRIC). The WSA2009 report indicates that it drew upon previous studies, being the Planning and NeedsFeasibility Study, the Detroit River International Crossing Study, and other transportationmodeling studies that were conducted further to the environmental process. These previousstudies were all considered in justifying the need for the DRIC.

ERL also reviewed the May 2010 Appendices of a later WSA Report, produced for the MichiganDepartment of Transportation, for the new crossing. The May 2010 Appendices provided oneadditional year of data points ending in 2008, as compared to the January 2009 Appendices,

which ended in 2007. The May 2010 report adjusted forecasts downward in 2009 as thepredictions from the earlier work had not borne out, though still projected continuous upwardgrowth after that point. But for this one minor difference between the Appendices, they areidentical in their methodologies and assumptions, and our conclusions apply equally to both.

Specifically, ERL was tasked with evaluating the travel demand forecasts of the Report and hasassembled a team of specialists to undertake this assignment consisting of Dr. Atif Kubursi(Professor of Economics, McMaster University and President of Econometric Research Limited),Dr. Pavlos Kanaroglou (Professor and Director of the School of Geography and Earth Sciences,McMaster University and Director of the McMaster Institute for Transportation and Logistics(MITL)), and Dr. Abe Mouaket (Transportation Engineer and President of Innovative Methods).

The CVs of the team members are included as an Appendix to the Report.

The ERL team focused on the structure of the travel demand model used, the data selected forestimation and projections, the assumptions made, the exact specification of the variousequations, the regression techniques chosen, the estimated results and forecasting scenarios.

ERL recognized right at the outset that the travel demand model used for this Study to forecastcrossing volumes builds upon earlier models developed originally for the Planning/Needs &


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Feasibility (P/N&F) Study in 2000, later updated as part of the Detroit River InternationalCrossing (DRIC) Study in 2004. ERL also recognized that the model travel forecasts are premised on a number of sub-models including a corridor growth analysis and several datacollection programs that included traffic counts, origin-destination and stated-preference surveys.The final model adopted by the WSA study team incorporates the findings and analyses from

these models.

The volumes of the traffic forecasts in the frontier region, however, are at the core of the Study.They are critical for justifying the need for the new crossing and these are dependent on theregression equations, assumptions and specifications, and the forecasts and projections of theindependent (explanatory variables) socioeconomic variables driving the future crossingsforecasts.

A brief review of the critical subcomponent models that were used to make the projections of thetraffic volumes is undertaken with the view of highlighting the key assumptions, data quality, thestructure of the equations, the estimation techniques, the regression results, the derived

projections of the travel demand model components, the constructed alternative scenarios and theinterpretation of the results.

Modeling Process

The WSA team provided in Chapter 5 of the Study a brief description of the models developedand updated as part of the P/N&F and DRIC studies as well as a general discussion of the databases used in calibrating the Travel Demand Model. A few Appendices are devoted to a broaderpresentation of these components and as such they form part of our review process.

The existing travel demand model used in the Study was originally developed in 2000 for the

P/N&F study and was then updated for the DRIC study in 2004. The P/N&F regional model wasdeveloped from three pre-existing models: (1) Southeast Michigan Council of Governments(SEMCOG) model covering southeast Michigan; (2) Windsor Area Long Range TransportationStudy (WALTS) model covering the greater Windsor area; and (3) the Ontario Ministry ofTransportation (MTO) Truck model, which focused primarily on Ontario, but also covered NorthAmerica.

The Previous DRIC study model was updated from the P/N&F model by moving from a 2000 to2004 base year to capture the major events that occurred after 2000 (such as 9/11, SARS, and theIraq War). As part of the study the international crossing trip tables were updated based on theobserved trends between 2000 and 2004, and the model was expanded to include a crossing

choice Logit model (which actually consists of three models: Multinomial Logit, Nested Logitand Mixed Logit) that assigned the international trips to the three crossings including the newalternative (DRIC) and estimated the willingness to pay at each of the crossings.

The General Update Framework of the Model

The manner in which the various parts fit within the overall structure of the travel demand modelare captured in Figure 1. Before displaying the model, it is useful to identify the nature of the


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updates to the model and the new changes introduced to the relevant databases. These changesand updates include:

Updating the road network to incorporate the new highway improvements in theSoutheast Michigan Council of Governments (SEMCOGs) 2035 Regional

Transportation Plan (RTP) and in the Windsor Area Long Range Transportation Study(WALTS) for the City of Windsor;

Incorporating the selected preferred alternative of the proposed new Detroit RiverInternational Crossing (DRIC) into the road network;

Calibrating the domestic trip tables on both U.S. and Canada sides to reflect most currenttraffic profile;

Updating the base international trip tables with the new passenger car origin-destinationsurvey conducted in April 2008; and the base commercial vehicle trip tables with thenational roadside survey/commercial vehicle survey (NRS/CVS) efforts which included a

commercial vehicle origin-destination survey performed by MTO in 2006;

Developing and integrating a new discrete choice model to represent the motoristsdecision-making behaviour based on a state-preference survey conducted in April 2008;

Calibrating the international and local models to the 2008 levels using the traffic countscollected on both the Canada and United States side of the existing crossing.

The travel demand model consists of a regional demand model and a cross-border traffic modelthat is further divided into commercial vehicle and passenger car model. Building upon theexisting DRIC study model, the original base year (2004) for the regional model was updated to

a 2008 base year. The modified base year trip tables for the commercial vehicle and passengercar markets were modified based on more recent Origin-Destination (O-D) survey data collectedwithin the corridor. The schematic presentation of the WSA model in Figure 1 highlights thestructure and flow of the system. This schematic structure is used to organize our evaluation ofthe model and results.

The base year regional model was calibrated to 2008 traffic counts and travel time data collectedfrom other regional studies. The calibrated regional model was then used to validate the crossingchoice model, which was constructed from the stated preference survey data collected in 2008 aspart of this study.

The future year network was updated by incorporating the new highway improvement programfrom the SEMCOGs 2035 regional transportation plan and from the WALTS on the Canadianside. The preferred alignment for DRIC alternative as directed by Transport Canada was codedinto the network and included the approaching roads on both sides of the crossing. However, thedomestic trip tables on the U.S. side were still based on tables in Windsor area that used theDRIC study trip tables which were updated to account for the latest demographic growth trends.


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The critical component in driving the volumetric forecasts came from the independent corridorgrowth analysis of the Centre for Spatial Economics.

6The future cross-border trip tables for both

commercial vehicles and passenger cars were created by applying growth indices developed inthe corridor growth analysis to the base year trip tables. In order to estimate the future trafficdemand on the new WGBC, traffic assignments were conducted with the updated networks and

future regional and cross-border trip tables. The regional traffic assignments were performedusing the user-equilibrium methodology, while the cross-border traffic was assigned using thevalidated discrete choice model developed as part of this study.

Figure 1 - Windsor Gateway Bridge Crossing Study Modeling Process Flowchart

6 Quoting the WSA Report The results from the corridor growth analysis performed as part of this study wereused as the basis for the development of the overall growth of the frontier traffic demand. (WAS 2009; 5-12).


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Source: Wilbur Smith Associates. January, 2009. Comprehensive Traffic and Toll Revenue Study: WindsorGateway Project. Pp 5-3.

The Baseline ContextIn any projection or forecast, the past is typically considered as the best guide for the future.Time series data are examined using regression analysis in order to identify and quantify thesystemic determinants of the dependent variables of interest during the period for which dataexists. The crucial dependent variables in this exercise are: The passenger traffic volumes andthe commercial vehicle volumes at the three existing crossings in the Windsor-Detroit-Sarniaarea, namely the Ambassador Bridge (AB), and Windsor-Detroit Tunnel (WDT), and the BlueWater Bridge (BWB).

It is obvious that the development of a new crossing (DRIC) in the region will have to be

contingent on a forecast that shows that traffic volumes in the future are likely to be larger thanthe existing traffic capacity. Equally important is that the new crossing will be based on a strongstated preference for a crossing that directly links to the highway network on both sides of theDetroit River and that it is cost effective (within the preferred trade-offs between cost and time).

The WSA team has developed its work with these objectives in mind. Unfortunately, the past didnot cooperate well with their plans. The recent developments in the region in the past decadehave been a tale of declining traffic, both for the passenger and commercial vehicle components.These declines are not exclusively conjectural (cyclical); they may reflect some deep structuraldevelopments and some unique changes that would not change course easily or quickly. Thesestructural and unique changes cannot be ignored; they have to be worked into the model and the

future projections must reflect them. Without taking these into consideration, the projections willreflect optimistic wishes and unjustifiably disregard significant lessons that must be learnt.

The Difficult Decade

The total volume of Canada/US border crossing traffic peaked in 1999/2000 with over 52.5million vehicles (of which 8.5 million were commercial vehicles). Between 2000 and 2008, thisvolume declined to less than 37.6 million vehicles (of which 7.3 million were commercialvehicles), showing a 28.5% total decline. The passenger car crossing declines (31%) werenotably larger and faster than commercial vehicle crossings (14%), and this is despite the

continuous growth in trade between the two countries.

The automobile frontier border crossing traffic also peaked in 1999 and has ever since beencontinuously decreasing with an almost 40% reduction in the Detroit and St. Clair River frontiertraffic in 2007 compared to the peak volumes in 1999. The commercial vehicle traffic has alsoreflected the downturn in the auto industry which has greatly affected the volumes of bordercrossing traffic. The details of the trends in frontier volumes of traffic are presented in Figure 2.


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The implicit rates of growth and decline over the period of 1972 to 2008 are displayed in Table1. Same-day Passenger vehicles which grew at the annual compound rate of 2.48% between1972 and 2000, and declined at the rate of 6.01% between 2002 and 2008. On the other hand,commercial vehicles frontier crossings that grew at the rate of 5.51% between 1972 and 2000,declined at the rate of 2.07% between 2002 and 2008.

Figure 2 Frontier Volume of Crossing Traffic by Type

Source: Statistics Canada

Table 1 Implicit Rates of Growth of Frontier Volume of Crossing Traffic

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRIC Project Forecast Refresh and UpdateAppendices. May 2010. Pp CG-8.

A number of factors have contributed to the reversal of past growth performance between 2000and 2008. While some of these factors may be dismissed as transitory and cyclical in nature, afew others are more likely to reflect structural factors and may well become ingrained into thenormal processes of the system.

Several socio-economic significant events have occurred since 2000 that have greatly affectedthe volumes of car and commercial traffic observed on the crossings. Some of these were


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recognized by the WSA team, but many were not considered and in all there is the presumptionthat their negative influences and impacts may not last

7. Below is a short list of those events that

we consider as likely to have long-lasting effects on traffic volumes, some of which were ignoredby the WSA team:

Opening of Detroit Casinos The opening of the MGM Grand Detroit Casino in July of1999 effectively ended the need for Detroit and other US residents to cross the border togamble at Casino Windsor. In addition, two new casinos have opened recently in Detroit.Canadian casinos have a few advantages over their US counterparts that include the factthat gaming wins in Canada are tax-free, Windsor is perceived to be a safer environmentthan Detroit and until recently a cheap Canadian dollar. But Canadian casinos also have afew disadvantages: the no smoking environment, no complimentary liquor, and the tollson crossings, longer driving time and now the passport requirement. It is not surprisingthat the opening of the new Detroit casinos has had a noticeable, if not permanent impacton discretionary traffic volumes;

The Stubborn Recession The economy took a significant downturn in 2000 after verystrong growth in the 1990s, from the dot-com bust, then the Enron collapse onDecember 2, 2002 and then the sub-prime debacle. What started as a real estate collapsewith housing prices falling over 30% in less than a year in 2008 (the early estimates putthe losses so far at over $2 trillion in the US alone), the sub-prime lending debacle led towidespread business foreclosures and personal bankruptcies as high risk lending togroups without sufficient resources to support their mortgage payments dragged severalbanks and individuals into insolvency (120 US banks so far and the tally keeps growing).It sank giant mortgage guarantors such as Freddie Mac and Fannie May when mortgageesabandoned their homes, as their values fell below the mortgaged value. This real estatecrisis could have been restricted to the balance sheets of mortgage lenders and guarantorsbut banks and investment banks bundled their risky (toxic) mortgages with other goodassets trying to hide the true risk content of these mortgages. They also believed that bypooling the sub-prime mortgages together, they would be insulated against the risk that asmall minority of mortgages might go sour - or if some went sour, the returns of theremaining mortgages would more than compensate for these losses. By all accounts,however, they essentially discounted to zero the probability of a housing crash, which ofcourse led to entire pools of mortgages becoming essentially worthless.8 Ripples andhiccups in the financial sector turned into tidal waves prompting Alan Greenspan to call ita Credit Tsunami. Unemployment rates in the US which were at record low levels of 3-4%, climbed up quickly exceeding 10% and staying stubbornly at or near this high leveldipping slightly as discouraged workers left the labour market.9 Detroit and Windsor

7 Source: IBI Group. Wilbur Smith Associates. DRIC Project Forecast Refresh and Update Appendices. May 2010.Pp41.8 For a discussion of the dangers of assuming that a highly unlikely event is in fact an impossible event, see NassimNicholas Taleb, 2007. The Black Swan: The Impact of the Highly Improbable. Taleb has also stated: Anyonewho knows anything about the history of banking (or remembers the 1982 Latin American debt crisis or the 1990ssavings and loan collapse) will tell you that the sub-prime crisis was so bound to happen.http://money.cnn.com/2008/03/31/news/economy/gelman_taleb.fortune/index.htm9 See International Labor Organization, January 28, 2009. Global Employment Trends Available at:http://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/documents/publication/wcms_101461.pdf


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recorded historically high levels of unemployment over the prevailing national averages.While the attraction of Detroit as an employment center for Windsor residents hadremained stable until 2006, it quickly contracted and many Canadians and local residentslost their jobs. The recovery is still slow and particularly in the job market. The prospectsof a job creating recovery has now been pushed further into the future and there are

serious doubts that the region will ever recover fully;

9/11, the Iraq War and the Afghanistan War The aftermath of September 11, 2001,and two related wars, has impacted the ease with which travelers can cross the border andhas also depressed the propensity for international discretionary travel;

SARS and Swine Flu epidemics in Toronto In 2003, the City, a popular touristdestination for Americans, was one of several global locations of the highly-publicizedepidemics. Impacts on tourism and vacation trips across the border were immediate andseem to have some long lasting impacts;

Appreciation of the Canadian dollar In 2007, the value of the Canadian dollar hitparity with the US dollar for the first time since the mid 1970s and for a short while iteven exceeded parity reaching $1.10 US per one Canadian dollar. While the rise in thevalue of the Canadian dollar vis--vis the US dollar makes travel to the US moreattractive for Canadians, it has the opposite effect for travel to Canada for Americans.From a work commuting perspective, the incentive for Canadians to work in the US willdecrease and Canadian exports to the US will rise in price and become less attractive. Onthe other hand, Canadians will be induced to increase their cross border shopping andimporting US goods. The real issue here is about the future value of the Canadian dollarin terms of US dollars. It is difficult to predict with any certainty this value, but theconsensus forecast puts this value at $1.07 Canadian dollars per $1 US dollar. This is stilla high value than the historical average or median over 50 years. If this appreciated valuewere to continue, lower traffic volumes could be expected;

Passport requirement The introduction of a passport requirement in mid 2010 oncross border traffic is turning out to be a major barrier to travel between the two countriesgiven the low propensity of US residents to acquire this document. It is believed thatupward of 50% of US citizens do not have a passport and are not likely to acquire onesoon;10

Increase in gasoline prices While gasoline prices have fluctuated widely, there is ageneral escalating trend. This is all the more likely with the increased realization that weare not adding to proven reserves what we are depleting and then there are the loomingemission charges and carbon taxes. Transportation volumes are quite sensitive to gas prices and the expected rise in these prices, as world wide scarcity rises, suggest that

10 most Americans do not have a passport. The number of Americans who have a passport, according to the StateDepartment, is 68 million, or around 22% of the population. That means roughly only 1 out of 4.5 Americans caneven visit Canada, let alone travel to anywhere else in the world. http://www.theexpeditioner.com/2010/02/17/how-many-americans-have-a-passport-2/#idc-container


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crossing volumes may decline in tandem with these expected increases in gas prices(depending of course on the elasticity of demand for travel with respect to gas prices);

11

Technological Change The Internet has reduced measurably the cost ofcommunication so much so that it is now the dominant means of human interaction. The

increased use of the Internet and the continuous decline in its cost has and will continueto boost its competitive attractiveness over traditional transportation modes of interaction.The increased share of services in GDP is another factor that would continue to decreasethe intensity of transportation. Today the US economy produces at least 10 times moreincome than in 1900 but weighs almost the same. This gave rise to the emergence of whatis referred to generally as the weightless economy;

The Disappearing Middle Class Income and wealth in both Canada and the UnitedStates have increasingly gravitated into the hands of the few rich. The poor have becomepoorer and the rich richer. The middle class suffered major losses in real income whereasthe top 20th percentile on the income distribution scale has expanded its income and

wealth shares. The rich typically fly and the poor rarely drive.

12

Passenger cars aregenerally owned and driven by the middle class. As globalization has been associatedwith income and wealth polarization, the middle class has shrunk. This is seen asresponsible for reducing the ranks of this class and the aftermath of the contractingnumbers of this class is expected to reduce driving in general and border crossings inparticular;13

Environmental Issues - Increased awareness of the impact of transportation on theenvironment is likely to convince people to travel less and to use other less intrusivemodes of transportation (e.g., trains). The implications of environmental awarenessbolstered by emission taxes, carbon charges, etc. must be factored into any forecast offuture traffic volumes in any jurisdiction.

The impacts of these events on annual crossing volumes have already become noticeable as isclearly shown in Figure 2. Since 2000, passenger car traffic volumes have decreased by 35% atthe Ambassador Bridge, 48% Detroit-Windsor tunnel, and 22%, at the Blue Water Bridge. Thecontinuation of these negative impacts on future volumes is quite likely as many of thesestructural factors continue to exert their influence. It only makes sense to treat these factors andtheir influences as hypotheses to be tested and their implications to be explored. Unfortunatelythe WSA report has either not done so or it did not do that properly.

11 See Gene Coperman in http://www.ccs.neu.edu/home/gene/peakoil/12See the information and graph inhttp://www.payscale.com/research/CA/Country=Canada/Salary/by_Method_of_Travel

13 The US Census Bureaus measurement of the Gini coefficient, a widely-used indicator of income inequality rosesteadily from a level of 0.388 in 1968 to 0.466 in 2001. Seehttp://www.census.gov/hhes/www/income/histinc/ie1.html


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Same Day Passenger Crossings

Three separate types of traffic volumes were identified and their growth rates were estimated.The three types include:

Passenger vehicle crossings occurring within the same day Passenger vehicle crossings with a trip duration exceeding the same day (overnight trips) Commercial truck crossings

Growth rates of each separate crossing volume is analyzed following the sequence that theCentre for Spatial Economics has presented its methodology, assumptions and results in theirReport to WSA.

People travel short or long distances for a variety of reasons whether for commuting to work,recreation, or other reasons. Many socioeconomic determinants can be postulated to influencethis travel. Typically same day travel is dominated by work consideration and this is a function

of such variables as income, exchange rates, cost of fuel, employment prospects, and many otherquantifiable or non-quantifiable factors.

The Centre for Spatial Economics used multivariate regression analysis to quantify thesedeterminants and projected the independent factors into the future in order to forecast the futurevolumes of cross border traffic in the Detroit Windsor region.

The specification of the regression equations is critical and we will focus on their structure,estimation, precision and results. These regression equations require data and that is where wewill begin our review and evaluation.

Same Day Passenger Car Crossings: Data Availability and Quality

Time series data are required for both the regression estimation and for forecasting. Theidentification and quantification of the influence of the independent socioeconomic (exogenousvariables) on the dependent variable (endogenous) which is here the volume of passenger carcrossings on the three Detroit River outlets is done through regression equations.

Annual historical time series crossing traffic data for the three Detroit River crossings by type ofvehicle (cars, trucks and buses) and by market segment (commuting, recreation, etc.) for 1972 to2008 are not available from one source or in the manner needed for the estimation. This required

a number of assumptions to prepare this data for the regression exercise. Some of theseassumptions are critical and can easily compromise the accuracy and reliability of the results.

The Annual automobile traffic volumes are available from the Public Border OperatorsAssociation (PBOA). This data is heavily used and has a general reputation of being accurate andreliable. It does not, however, provide the purpose of the trip. This has to be drawn from othersources. A good source is Statistics Canada International Travel Survey that is conductedannually relating to the travel characteristics of US residents entering Canada and Canadian


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residents returning from overseas and the US. Information on same day and overnight visits byport (Windsor, Sarnia, etc) by mode of travel (cars, buses, etc.) and other relevant characteristicsare available from this Survey. Unfortunately, this separation between same day and overnighttrips is only available until 1997. After 1997 both types of trips are lumped together for theDetroit/Sarnia crossings.

The Center for Spatial Analysis uses the proportions of overnight to same day crossings for theAmbassador Bridge and Windsor-Detroit Tunnel in 1997 to separate same day crossings fromovernight crossings for subsequent years. Given that a great deal has changed since 1997,particularly factors that would influence overnight crossings and same day crossings differently,real questions can be raised about the permanency (constancy) of this share over time.

A number of additional assumptions were made to prepare the data required for the estimationand projections. The most critical and questionable of these include:14

Same day and overnight passenger car travelers characteristics of those entering the USfrom Canada are the same as for travelers entering into Canada from the US.

Automobile occupancy rates for both US and Canadian travelers are identical. This isperhaps not a critical assumption but it can still bias the results given the escalation in thecost of fuel, the rise in the cost effectiveness of travel of smaller parties and the differentpurposes motivating the parties to travel.

Non-Canadian/US residents traveling into Canada have the same travel characteristics asthose surveyed. This is untrue. Though the proportions of these to the total are small andso may not make a major difference in the results, it is not correct or reasonable to expectnon Canadian and US travelers to exhibit the same characteristics as those surveyed.They generally travel for different reasons and purposes than others who were surveyed.

The Michigan Ontario Border Crossing Survey results of 2000 were used to generate volumeflows and characteristics for later years. The most glaring inherent assumption was thatpertaining to the proportion of commute/work trips in the survey as being representative of thatproportion for the entire year and beyond.

The Origin-Destination survey trip purpose data was also used to split the passenger car trafficfor 2008 with an adjustment to account for weekends. The interim years between 2000 and 2008were interpolated based on the data in 2000.

These assumptions may have been necessary to generate time series data for estimation purposes. Nonetheless these assumptions introduce an element of inaccuracy that certainly both coloursand compromises the reliability and usefulness of the exercise.

Other data sources used present different challenges and problems. Census data from StatisticsCanada was used to estimate the number of Canadians living in the Windsor CensusMetropolitan Area (CMA) that were employed outside Canada. This information was assumed

14 These assumptions are listed in (WSA 2010; CG-6).


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to be representative of the number of commute/work trips at Windsors crossings. Furthermore,this information is only available on a five year basis. The last Census was in 2006. Using 2001as a base year and the estimate of commute/work trips of each census year up to 2001 base yearwas applied to estimate future years commute/work crossings at the two Windsor crossings.Assuming that the same proportion in 2001 would apply for all subsequent years is a significant

assumption which is not very reliable.

Same Day Passenger Car Crossings: The Regression Equations and Results

The distinction between same day commuting and overnight traffic was motivated by the factthat different determinants explain these two separate trips. Several a priori assumptions weremade and tested by the Center. The same day work related crossings were assumed to dependexclusively on employment and population. The presumption here is that other factors such asexchange rate fluctuations, security concerns, and the price of gas are not importantconsiderations for this segment of traffic.

The Centre claims that multiple possible socioeconomic variables were tested (200 multivariateequations were modeled with permutations of the independent socioeconomic variables for eachsame day passenger vehicle crossing purpose)15 to determine a statistically significant historicalcorrelation with the border crossing volumes. However, this is only a claim. The Report andAppendix C do not report on any of these estimated equations.

The Centre has chosen to report on only one equation for the frontier and for each traffic volumetype based on the socioeconomic variables that exhibited the best explanatory power based onwhat it claims to be the outcome of its qualitative and quantitative assessments of the regressionresults.

The regression results displayed in Table 2 show that 91% of the variations in the first equationare explained by Michigan and Ontario employment alone (Adjusted R2). The t-statistic is high,but this is misleading because of the possibility of misspecification of the estimated equation. (t-statistics are a measure of robustness and significance of the explanatory variable as it representsthe number of times the estimated coefficient of the independent variable exceeds its standarderror. If the estimated coefficient is only equal to two times its standard error or less it isconsidered to be imprecise.)

It is reasonable to question a specification that shows one variable explaining this much of thevariation of same day traffic (commute/work related) on its own. It is typically the case that in aregression equation with missing variables the one single explanatory variable picks up theimplicit influences of the variations in these missing variables. We are emboldened to claim thisgiven that the second equation of other same day traffic is sensitive to employment in the localzone (while the commute/work equation is not) and to the events in September 11, 2001.

Interestingly the second equation is negatively related to local employment. The story advanced by the Center perhaps applies more to the first category rather than to the second. What is

15 Footnote 5 to the WSA 2010; CG-13).


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worrisome is that the single determinant in the first equation is a variable that typically displays a positive trend which would, as we shall see later, bias the projections of this traffic volumeupward without a single negative influence of the type experienced and reflected in the volumesof crossings after 1999.

It would have been possible to settle this argument if other typical regression statistics wereprovided such as the Durbin Watson (DW) coefficient or any other similar coefficient of anyautocorrelation in the error terms. To properly evaluate this would require a picture of the errorspattern. Any systematic display in these errors would have pointed out immediately if there weresystematic errors indicative of autocorrelation in the errors because of the influence of missingvariables.

Table 2 Regression Estimates for Same Day Crossings

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRIC Project Forecast Refresh and Update

Appendices. May 2010. Pp CG-14.

The predicted and actual volumes are displayed in Figure 3 and show that the estimated equationfits well the actual data. What is relevant here is that fitted equation fits both the upward trendsbefore 2000 and the declining trends after 2000.


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Figure 3 Actual and Regression Estimates of Same Day Crossings (1987=100)


Historically, both the population of Ontario and that of SEMCOG show positive trends, thoughmore in the case of Ontario than for SEMCOG. However, when the two populations arecombined, the Ontario population growth (driven by immigration) dominates (Figure 4) and theresultant population exhibits a positive and upward trend.

We question whether this addition is a coincidental construction. If one wants to forecast largefuture volumes of traffic it certainly helps to have the independent variable show an upwardpositive trend (slope). The employment trends show an upward trend until 2006. Following thatthere is a visible decline. If data were extended to 2010 this decline would be more pronounced(Figure 5). Surprisingly none of these negative observations after 2006 are reflected in forecasts(projections) of the employment trends. The projected values of this employment variable simply

show rising trends as if the structural events in the last decade were simply short-termaberrations that are not likely to endure even in the early period of the forecast.

The impact of 9/11 is singled out as a determinant of the non-work related same day crossings. Itinfluences this volume in a negative way. The Center claims that the influence of this event will be visible for a while but it will transpire throughout a generation span assumed toprogressively decline until becoming non-influential by 2034, i.e., the dummy variableprogressively declines to the value of zero then. It is not clear how this decline is determined. It


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is not a geometrical decline, nor is it an arithmetic decline; it would have helped to see an exactspecification of how this influence dissipates over time.

Figure 4 Historical Indexed Population Trends

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRIC Project ForecastRefresh and Update Appendices. May 2010. Pp CG-10.

Both figures 5 and 6 present the historical indexed employment trends in the Provincial economyof Ontario, State economy of Michigan and other local economies in Windsor and Sarnia.Nothing is presented about the employment trends in the Detroit area alone. This selective choiceof independent variables and trends does not instill confidence in the analysis and raisesquestions about whether the objectives of the study may have trumped the scientific basis of theexercise.

In Figure 6, SEMCOG population is presented but not employment. To what extent the negativetrends in the employment variable has played a role in dismissing or excluding it from theanalysis of trends, projections and of course from being selected as a determining factor is notexplained in the report. .


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Figure 5 Historical Indexed Employment Trends

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRIC ProjectForecast Refresh and Update Appendices. May 2010. Pp CG-11.

It is small wonder then that the baseline forecasts in Figure 7 show an upward future trend of thevolume of traffic in the frontier area of passenger cars same day traffic despite the fact that in theearlier period preceding the forecast there was a major trough in these volumes. It is here that the projections become questionable. It is simply unacceptable to dismiss the earlier decade as

irrelevant and equally unacceptable to premise the projections on only those indexed values thatare positive. If the past is any indicator of the future, a similar pattern would prevail and thepicture that emerges would show a different profile than the one the Center wants us to accept.


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Figure 6 Forecast of Population and Employment Trends


Figure 7 Baseline Forecast of Frontier Same Day Crossings

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRIC Project Forecast Refreshand Update Appendices. May 2010. Pp CG-18.


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The Center claims that other explanatory variables were tested such as other population andemployment socioeconomic variables pertaining to Michigan and/or Ontario, dummy variables(including the Detroit Casinos, the Windsor Casino, the 9/11 impact, the impact of the FreeTrade Agreement, the foreign exchange rate, the State and Provincial GDPs). However, theseclaims were not demonstrated. Instead it was asserted that the regression results indicated that

..all but the previously mentioned [combined employment in Michigan and Ontario for the firstequation] and [the local employment and 9/11 in the second equation] socioeconomic variableswere the best suited variables for explaining the levels of total same-day traffic volumes.

16

This study sought to investigate whether a multi-billion dollar investment that the tax-payers ofCanada, particularly Ontario, and private domestic businesses would pay for, is justified byexpected increases in traffic volumes over existing capacity. It is not acceptable to make claimsabout results that are not displayed and made in a transparent way for others to evaluate and/orreplicate.

Overnight Passenger Car Crossings: The Regression Equations and Results

These crossings represent a modest share of total passenger car crossings. The average sharebetween 1972 and 2008 was 19% and has since risen to 22% in recent yeas as work related sameday passenger cars crossings declined.

The overall trend of these crossings was positive for most of the period 1972-2008. In 2007 and2008 the volume of passenger car crossings declined.

A number of key variables are assumed to be potential explanatory and predictive variables.These include the populations of Michigan and Ontario, the employment levels in both of theseareas, their real GDP, the exchange rate and a dummy variable for 9/11. The Center has claimedthat different pairings of these variables were tested.

Given the number of observations, it is not clear why pairings of two and not more than twoexplanatory variables were used in the regression equations. Again it is claimed that in the endthe greatest explanatory power of historical overnight passenger car crossings came from thecombined populations of Ontario and Michigan. This variable explained only 68% of the totalvariation in the dependent variable. This is not a whole lot in time series regressions. It is alsoclaimed that none of the other variables explained the brief rise above and the fall below the longterm trend. Indeed it would have been helpful to see this claim demonstrated.

It is interesting to note that the exchange rate was capable of explaining 92% of the variation inthe share of overnight crossings, but failed to explain the dip in the share that occurred in thelatter half of the 1990s. It is curious that the combined population and the exchange rate thatcould have dealt with this problem were not tried and presented. Unfortunately this selectivepresentation of the results is not very helpful. It is also small wonder that the regression equationwith only the combined populations (with an upward trend) has over-estimated the volume in2009 by a large margin (the predicted volume using the regression equation is 3.47 million while

16 See (WSA 2010; CG-16).


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the actual number was 2.48 million). It is easy to wonder whether another variable such as theappreciating Canadian dollar could have captured this decline.

The regression results in Table 3 show that the adjusted R2 is not impressive (about 68%). The t-score is high and statistically significant (8.74), but it is not clear that this is the outcome of its

independent explanatory power or the outcome of other missing variables.

Table 3 Regression Results for Overnight Crossings


It is here that one could also wonder why other functional forms were not specified andestimated. The linear structure is simply inappropriate as is clear in Figure 8. If the real issue isforecasting accuracy, then other statistical specifications such as Vector Auto Regression (VAR),Box-Jenkins, ARIMA, etc should have been used. Earlier studies did that with some success andgood outcomes, but for some unexplained reason, it has not been completed with this most recentreport.

There is nothing surprising about the lack of concordance between the actual and predictedvalues in Figure 8. The actual values show significant fluctuations, the predicted values based ona smoothly rising population shows a smooth positive trend in overnight passenger car crossings.This is precisely why it is inadmissible to use this equation in predicting this variable. Otherspecifications would be better predictors, particularly any with an independent variableexhibiting some fluctuations in its values that mirror the ones displayed by the dependentvariable.


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Figure 8 Actual and Estimated Historical Indexed Overnight Crossings


Figure 9 Baseline Forecast of Michigan and Ontario Population



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Nothing but a positive and continuous trend in the volume of overnight passenger car crossingscan come from the baseline forecasts using the projections in Figure 9. Despite the evidentfluctuations and the dip in the volumes of crossings in overnight passenger vehicles, the forecastis a continuously rising volume of these crossings as is clear in Figure 10 below. It is true thatthe slope of the rise is limited but there are serious doubts as to the validity of using a

continuously rising explanatory variable to predict when the past is essentially a truly camelhumped distribution. While some adjustments were made to the levels forecasted for 2009 and2010, these were insufficient and ad hoc.

Figure 10 Baseline Forecast of Overnight Crossings

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRIC Project Forecast Refresh and

Update Appendices. May 2010. Pp CG-22.

Commercial Vehicle Crossings: The Regression Equations and Results

Commercial vehicles accounted for over 27% of the total vehicle crossings along the frontier in2007 and 2008. The importance of this market segment has grown over the entire period of1972-2008. The share of this market segment increased from about 11% in early 1970s to the


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present 27%. The most significant growth occurred in the 1990s following the Free TradeAgreement (FTA) and NAFTA.

The commercial vehicle crossings along the frontier are primarily of the long haul category witha small share representing local to local trips. It is also true that a good share of the commercial

vehicle trips are related to the motor vehicles and parts trade across the frontier. About a third ofall commercial vehicle crossings were related to this trade given that Ontario and Michigan weremajor producers of motor vehicles and parts. Michigan still represents about 22.1% of all USmotor vehicles and parts while Ontario continues to represent 66.6% of all Canadian production.

The recent recession decimated the auto sector. Employment, production and sales fell by over30%. As well, Michigan and Ontario are losing market share in this sector suggesting that in theabsence of other substitutes, the trade volumes between the US and Canada can be expected todecline. More noticeable and of significant implication for crossings of all types is the loss ofmarket share in this sector by both Windsor and Detroit. Even if this sector were to recover, it isby no means certain that Detroit and Windsor would reclaim their past shares in this sector.

The rate of increase in the trade volumes between the two countries has been steep andmagnitudes increased in multiples of past values. Recently, the recession has cut deep into thesetrends as is depicted in Figure 11. The real question is how long the current recession will lastand to what extent does the recent appreciation in the Canadian dollar cut into these volumes.

Figure 11 Historical Indexed Trade Trends

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRIC Project ForecastRefresh and Update Appendices. May 2010. Pp CG-12.

The trade structure between Ontario and Michigan and between Canada and the US is changingtoo. Other products are gaining importance (Machinery and forestry products) and replacing theauto sector as the dominant tradable commodities. But whatever the structure or volume of trade


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is, it is this key, and unknowable, variable that is likely to continue to explain the volume ofcommercial vehicle crossings along the frontiers.

The explanatory variables of the volume of commercial vehicle crossings along the frontier arethe turnover of Ontarios foreign trade and the exchange rate. Both of these variables are highly

significant. The Ontario foreign trade turnover has a t-statistic of over 29.4 and that of theexchange rate of about 6. We are not sure about the sign of this coefficient as we are not clearabout the definition of the exchange rate used. If it is defined as the price of one US dollar inCanadian dollars, it should be negative. But combining exports and imports adds anothercomplication.

Table 4 Regression Results for Commercial Vehicles Frontier Crossings


The adjusted R2 is quite high and without doubt this is the best regression fit of all the threetraffic components. It is not surprising therefore to see that the actual and estimated curves arequite close and the predicted volumes tracks well and fully the actual data in Figure 12.

Figure 12 Actual and Estimated Commercial Vehicle Frontier Crossings

Source: Centre for Spatial Economics. Wilbur Smith Associates. DRICProject Forecast Refresh and Update Appendices. May 2010. Pp CG-25.


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The same problems alluded to in earlier sections afflict the projections of the independent(exogenous) variables driving the forecast in the case of commercial vehicle crossings forecasts.Again the predicted turnover of trade is an upward and smooth trend and it alone is carrying the brunt of the forecasts of the commercial vehicle crossings (Figure 12). We are not sure what

happened to the exchange rate variable. It may have been dropped as in other forecasts onaccount of the incorrect assumption that the impact of its fluctuations are presumed to be of ashort term nature - but are they?

Figure 12 Forecast of Ontario Foreign Merchandise Trade


Predicting the future turnover of Ontarios foreign trade is not a simple task. The US real GDP isassumed correctly to be one of the major determinants but so are the exchange rate and a dummyfor 9/11. But a real issue remains, what forecast to use of the US real GDP?

Given the close relationship between trade turnover and commercial vehicle crossings and thecommon patterns they share as displayed in Figure 13, correctly predicting the turnover offoreign trade may provide a solid anchor for predicting commercial vehicle crossings.


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Transport Canada provided the Center with long term projections for the US which they acquiredfrom the Conference Board of Canada, Infometrica and Global Insight. The Center was nothappy with those projections and preferred to use its own, given the greater consistency theirprojections have with the US Congressional Budget Office (CBO).

Typical CBO projections are for 10 years and the Congressional Budget Office has projected thepotential annual growth rate of real GDP to fall from 4% in the early 2000s to 2.4% in 2018. Butback in 2000, the CBO prepared a 75 year projection to assess long term budgetary implicationsof Social Security and Medicaid. The projections portray a declining path of growth rates till2020 and further declines to 2050 at a rate of growth of less than 1% per year until 2075. Theselow growth rates are the result of an anticipated decline in the working age population (20 to 64years) and a concurrent decline of productivity growth to less than 1% per year (Figure 14). Thedifferent projections of US and Canadian real GDP by different consulting firms were contrastedwith the Centers and this comparison is displayed in Figure 15.

Figure 13 Historical Trends in Indexed Commercial Vehicle Crossings

and Ontario Trade


Surely the Centers projections are lower and more consistent with the CBOs. This hasimplications on Ontarios trade and therefore on overnight commercial vehicle crossings alongthe frontier.


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Figure 14 Historical and Projected Potential Real GDP Growth in the United States

and Canada, Annual Percent Data from 1950 to 2050


Figure 15 - A Comparison of Projected Real GDP Growth in the United States,

Annual Percent Change from 2005 to 2051



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The line of influence captured by the regression equation in Table 4 suggests that GDP growthinfluences trade and the latter influences commercial vehicle crossings. It is obvious that declinesin US real GDP growth rates are bound to reduce the growth of Ontario exports to the US and inturn limit the growth of overnight commercial vehicle crossings.

The trajectory path of the forecasted values in Figure 16 does not reflect these lines of influence.To the contrary, the projected rates of growth of commercial vehicles follow a steep upwardrising trend. Again the influence of the exchange rate and other relevant variables withstatistically significant t-scores has disappeared unjustifiably from the forecasting equation. Thevolume of commercial vehicle crossings doubles in 20 years and continues to grow linearly upuntil 2064 where it reaches 3.5 times the baseline volume in contrast to the historical record andthe projected trends in the explanatory variable.

Figure 16 Commercial Vehicle Frontier Crossings Forecast



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Alternative Forecasts and Risk Analysis

The future is uncertain and the projected values are subject to errors. Some are embodied in theestimated coefficients (with standard errors) and others are about the trends in the exogenous(independent) variables.

The Center has chosen to use an outmoded and now generally unaccepted way to deal with thefuture and risks. Using arbitrary pessimistic and optimistic variations does not help much. Werethe investment values at stake in the order of magnitude of a few million dollars, the use ofsophisticated risk analysis may not be warranted. The expected new investment in the newbridge is likely over $5 billion in total, and probably more. Forecasting errors are quite costlyand simple forecasts can not and should not underpin massive investments of the kind and valueexpected to be made in the new crossing.

We are of the opinion that a full and thorough risk assessment procedure is necessary andwarranted. The current alternative forecasts are not consistent with the current standard risk

analysis procedures. The latter calls for using the standard errors in the regression equations anddifferent probability distributions assigned to the exogenous variables. A standard tool is @RISKwhich is now widely used and is the standard tool in this area.

The procedures used by the Center to bracket its projections are presented below in a number offigures. Both the optimistic and pessimistic forecasts are outlined in Figure 17 through Figure 20.With the exception of the low scenario for overnight passenger vehicles crossings of the frontier,where the end of the period forecast of the volume of crossings is lower than the one in 2008, allother forecasts show that even the low scenarios project higher future volumes of crossings.

A minimum regret strategy is one that is typically conceived to protect the investors under a

worst case scenario and it generally postulates the largest risk exposure. The scenarios are notconstructed to deal with these downside risks or with the probability of their occurrence. Theabsence of this probabilistic framework undermines the usefulness and credibility of the existingscenarios.

The what if and sensitivity analyses in Chapter 7 are not sufficient to deal with the risksembedded in this massive project and the type of forecasts and analyses undertaken. There is noway that sensitivity analysis, however useful it may be, can substitute for the proper risk analysisthat we are arguing for.


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Figure 17 - Index of Real GDP in the United States (1981=100) for the

Baseline, High and Low Projection Alternatives



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Figure 18 Same Day Passenger Vehicle Crossings Forecast Alternative Scenarios



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Figure 19 - Indexed Forecast Corridor Growth for the Alternative Scenarios:

Overnight Passenger Vehicle Crossings (1987=100), Selected Years



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Figure 20 - Indexed Forecast Corridor Growth for the Alternative Scenarios:

Commercial Vehicle Crossings (1987=100), Selected Years



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The Stated Preference Model

The expected future volume of traffic on the new crossing (DRIC) draws on the Centresforecasts and the Stated Preference Model developed and implemented by Resource SystemsGroup Inc. (RSG). The results of the stated preference model, the revealed preference survey and

the Origin-Destination surveys are used to allocate traffic over the four crossings. Thewillingness-to-pay estimates are also used to gauge the sensitivity of the traffic volumes andrevenues to different toll rates. Unfortunately the tools are not sufficiently or appropriatelydeveloped to allow this usage.

This section provides comments on a series of discrete choice analysis models that wereestimated with stated preferences data collected for the purpose of evaluating the sensitivity oftravelers crossing both the Detroit River and the St. Clair River to tolls and time. The statedpreferences survey through which data were collected used an orthogonal experimental design,implying that the independent variables used in the estimated discrete choice models wereuncorrelated. It is not clear to us at this stage how survey participants were randomly selected for

inclusion in the sample. Like any other econometric modeling activity, a random sample isnecessary, if one is to avoid bias in the parameter estimates.

It is important to note that discrete choice mo

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